Influence of Dispersion Interactions on the Polymorphic Stability of Crystalline Oxides

The accurate determination of relative phase stabilities using DFT methods is a significant challenge when some of these can vary by only a few kJ/mol. Here, we demonstrate that for a selection of oxides (TiO₂, MnO₂, and ZnO) the inclusion of dispersion interactions, accomplished using the DFT-D3 correction scheme, allows for the correct ordering and an improved calculation of the energy differences between polymorphic phases. The energetic correction provided is of the same order of magnitude as the energy difference between phases. D3-corrected hybrid functionals systematically yield results closest to experiment. We propose that the inclusion of dispersion interactions makes a significant contribution to the relative energetics of polymorphic phases, especially those with different densities, and should therefore be included for calculations of relative energies using DFT methods.

Exfoliation Energy of Layered Materials by DFT-D: Beware of Dispersion!

In this work, we have computed the exfoliation energy (the energy required to separate a single layer from the bulk structure), the interlayer distance, and the thermodynamic state functions for representative layered inorganic minerals such as Brucite, Portlandite, and Kaolinite, while leaving the more classical 2D transition-metal dichalcogenides (like MoS₂) for future work. Such materials are interesting for several applications in the field of adsorption and in prebiotic chemistry. Their peculiar features are directly controlled by the exfoliation energy. In materials without cations/anions linking different layers, the interactions keeping the layers together are of weak nature, mainly dispersion London interactions and hydrogen bonds, somehow challenging to deal with computationally. We used Hartree-Fock (HF) and density functional theory (DFT) approaches focusing on the role of dispersion forces using the popular and widespread Grimme's pairwise dispersion schemes (-D2 and -D3) and, as a reference method, the periodic MP2 approach based on localized orbitals (LMP2). The results are highly dependent on the choice of the scheme adopted to account for dispersion interactions. D2 and D3 schemes combined with either HF or DFT lead to overestimated exfoliation energies (about 2.5 and 1.7 times higher than LMP2 data for Brucite/Portlandite and Kaolinite) and underestimated interlayer distances (by about 3.5% for Brucite/Portlandite). The reason is that D2 and D3 corrections are based on neutral atomic parameters for each chemical element which, instead, behave as cations in the considered layered material (Mg, Ca, and Al), causing overattractive interaction between layers. More sophisticated dispersion corrections methods, like those based on nonlocal vdW functionals, many body dispersion model, and exchange-hole dipole moment not relying on atom-typing, are, in principle, better suited to describe the London interaction of ionic species. Nonetheless, we demonstrate that good results can be achieved also within the simpler D2 and D3 schemes, in agreement with previous literature suggestions, by adopting the dispersion coefficients of the preceding noble gas for the ionic species, leading to energetics in good agreement with LMP2 and structures closer to the experiments.

Evolutionary Algorithm-Based Crystal Structure Prediction for Copper(I) Fluoride

Despite numerous experimental studies since 1824, the binary copper(I) fluoride remains unknown. A crystal structure prediction has been carried out for CuF using the USPEX evolutionary algorithm and a dispersion-corrected hybrid density functional method. In total about 5000 hypothetical structures were investigated. The energetics of the predicted structures were also counter-checked with local second-order Møller-Plesset perturbation theory. Herein 39 new hypothetical copper(I) fluoride structures are reported that are lower in energy compared to the previously predicted cinnabar-type structure. Cuprophilic Cu-Cu interactions are present in all the low-energy structures, leading to ordered Cu substructures such as helical or zig-zag-type Cu-Cu motifs. The lowest-energy structure adopts a trigonal crystal structure with space group P3₁ 21. From an electronic point of view, the predicted CuF modification is a semiconductor with an indirect band gap of 2.3 eV.

Extracting Crystal Chemistry from Amorphous Carbon Structures

Carbon allotropes have been explored intensively by ab initio crystal structure prediction, but such methods are limited by the large computational cost of the underlying density functional theory (DFT). Here we show that a novel class of machine-learning-based interatomic potentials can be used for random structure searching and readily predicts several hitherto unknown carbon allotropes. Remarkably, our model draws structural information from liquid and amorphous carbon exclusively, and so does not have any prior knowledge of crystalline phases: it therefore demonstrates true transferability, which is a crucial prerequisite for applications in chemistry. The method is orders of magnitude faster than DFT and can, in principle, be coupled with any algorithm for structure prediction. Machine-learning models therefore seem promising to enable large-scale structure searches in the future.